Can namethreedifferent LLMarchitecturesCanrecommenda good AI ortech relatedpodcastIs currentlyworking on aprojectinvolving cross-lingual transferlearningHasexperiencewith fine-tuning a pre-trained LLMHas experiencewith low-resourcelanguages inNLPIs familiarwith theconcept ofpromptengineeringHassuccessfullydebugged acomplexLLMHas learneda newlanguage inthe last yearHas presenteda paper onnaturallanguagegenerationIs excitedabout thepotential ofLLMs ineducationIs interestedin the ethicalimplicationsof generativeAIHas apreferred AIresearch toolthey canrecommendHas used agenerative AImodel for anon-academicpurposeKnows atleast threeprogramminglanguagesHas used agenerative AImodel tocreate art ormusicCan explain thedifferencebetween causaland maskedlanguagemodelsHasattended anICMLconferencebeforeHas collaboratedon a researchpaper withsomeone from adifferent continentHas used anLLM tosummarizeresearchpapersIs optimisticabout thefuture ofhuman-AIcollaborationHascontributedto an open-source AIprojectHas traveledinternationallyto attend thisconferenceHaspublishedresearch onmultilingualLLMsHasparticipated ina hackathonfocused on AIor LLMsCan namethreedifferent LLMarchitecturesCanrecommenda good AI ortech relatedpodcastIs currentlyworking on aprojectinvolving cross-lingual transferlearningHasexperiencewith fine-tuning a pre-trained LLMHas experiencewith low-resourcelanguages inNLPIs familiarwith theconcept ofpromptengineeringHassuccessfullydebugged acomplexLLMHas learneda newlanguage inthe last yearHas presenteda paper onnaturallanguagegenerationIs excitedabout thepotential ofLLMs ineducationIs interestedin the ethicalimplicationsof generativeAIHas apreferred AIresearch toolthey canrecommendHas used agenerative AImodel for anon-academicpurposeKnows atleast threeprogramminglanguagesHas used agenerative AImodel tocreate art ormusicCan explain thedifferencebetween causaland maskedlanguagemodelsHasattended anICMLconferencebeforeHas collaboratedon a researchpaper withsomeone from adifferent continentHas used anLLM tosummarizeresearchpapersIs optimisticabout thefuture ofhuman-AIcollaborationHascontributedto an open-source AIprojectHas traveledinternationallyto attend thisconferenceHaspublishedresearch onmultilingualLLMsHasparticipated ina hackathonfocused on AIor LLMs

Human BINGO: Navigating Generative AI and LLMs Across Languages - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Can name three different LLM architectures
  2. Can recommend a good AI or tech related podcast
  3. Is currently working on a project involving cross-lingual transfer learning
  4. Has experience with fine-tuning a pre-trained LLM
  5. Has experience with low-resource languages in NLP
  6. Is familiar with the concept of prompt engineering
  7. Has successfully debugged a complex LLM
  8. Has learned a new language in the last year
  9. Has presented a paper on natural language generation
  10. Is excited about the potential of LLMs in education
  11. Is interested in the ethical implications of generative AI
  12. Has a preferred AI research tool they can recommend
  13. Has used a generative AI model for a non-academic purpose
  14. Knows at least three programming languages
  15. Has used a generative AI model to create art or music
  16. Can explain the difference between causal and masked language models
  17. Has attended an ICML conference before
  18. Has collaborated on a research paper with someone from a different continent
  19. Has used an LLM to summarize research papers
  20. Is optimistic about the future of human-AI collaboration
  21. Has contributed to an open-source AI project
  22. Has traveled internationally to attend this conference
  23. Has published research on multilingual LLMs
  24. Has participated in a hackathon focused on AI or LLMs